scholarly journals Panama’s Current Climate Replicability in a Non-Hydrostatic Regional Climate Model Nested in an Atmospheric General Circulation Model

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1543
Author(s):  
Reinhardt Pinzón ◽  
Noriko N. Ishizaki ◽  
Hidetaka Sasaki ◽  
Tosiyuki Nakaegawa
Keyword(s):  
Regional Climate Model ◽  
Air Temperature ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
Horizontal Resolution ◽  
Temperature And Precipitation ◽  
Current Climate

To simulate the current climate, a 20-year integration of a non-hydrostatic regional climate model (NHRCM) with grid spacing of 5 and 2 km (NHRCM05 and NHRCM02, respectively) was nested within the AGCM. The three models did a similarly good job of simulating surface air temperature, and the spatial horizontal resolution did not affect these statistics. NHRCM02 did a good job of reproducing seasonal variations in surface air temperature. NHRCM05 overestimated annual mean precipitation in the western part of Panama and eastern part of the Pacific Ocean. NHRCM05 is responsible for this overestimation because it is not seen in MRI-AGCM. NHRCM02 simulated annual mean precipitation better than NHRCM05, probably due to a convection-permitting model without a convection scheme, such as the Kain and Fritsch scheme. Therefore, the finer horizontal resolution of NHRCM02 did a better job of replicating the current climatological mean geographical distributions and seasonal changes of surface air temperature and precipitation.

scholarly journals Assessing the Effects of Spatial Resolution on Regional Climate Model Simulated Summer Temperature and Precipitation in China: A Case Study

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Xin-Min Zeng ◽  
Ming Wang ◽  
Yujian Zhang ◽  
Yang Wang ◽  
Yiqun Zheng
Keyword(s):  
Regional Climate Model ◽  
South China ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Northern China ◽  
Horizontal Resolution ◽  
Vertical Resolution ◽  
Humid Climate ◽  
Entire Area

The regional climate model, RegCM3, is used to simulate the 2004 summer surface air temperature (SAT) and precipitation at different horizontal (i.e., 30, 60, and 90 km) and vertical resolutions (i.e., 14, 18, and 23 layers). Results showed that increasing resolution evidently changes simulated SATs with regional characteristics. For example, simulated SATs are apparently better produced when horizontal resolution increases from 60 to 30 km under the 23 layers. Meanwhile, the SATs over the entire area are more sensitive to vertical resolution than horizontal resolution. The subareas present higher sensitivities than the total area, with larger horizontal resolution effects than those of vertical resolution. For precipitation, increasing resolution shows higher impact compared to SAT, with higher sensitivity induced by vertical resolution than by horizontal resolution, especially in rainy South China. The best SAT/precipitation can be produced only when the horizontal and vertical resolutions are reasonably configured. This indicates that different resolutions lead to different atmospheric thermodynamic states. Because of the dry climate and low soil heat capacity in Northern China, resolution changes easily modify surface energy fluxes, hence the SAT; due to the rainy and humid climate in South China, resolution changes likely strongly influence grid-scale structure of clouds and therefore precipitation.

scholarly journals Regional Climate Model Simulations of U.S. Precipitation and Surface Air Temperature during 1982–2002: Interannual Variation

2007 ◽  
Vol 20 (2) ◽  
pp. 218-232 ◽  
Author(s):  
Jinhong Zhu ◽  
Xin-Zhong Liang
Keyword(s):  
Regional Climate Model ◽  
Air Temperature ◽  
Interannual Variation ◽  
Climate Model ◽  
Regional Climate ◽  
Phase Relationship ◽  
Surface Air Temperature ◽  
Department Of Energy ◽  
Precipitation Pattern ◽  
Interannual Variations

Abstract The fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5)-based regional climate model (CMM5) capability in simulating the interannual variations of U.S. precipitation and surface air temperature during 1982–2002 is evaluated with a continuous baseline integration driven by the NCEP–Department of Energy (DOE) Second Atmospheric Model Intercomparison Project Reanalysis (R-2). It is demonstrated that the CMM5 has a pronounced downscaling skill for precipitation and temperature interannual variations. The EOF and correlation analyses illustrate that, for both quantities, the CMM5 captures the spatial pattern, temporal evolution, and circulation teleconnections much better than the R-2. In particular, the CMM5 more realistically simulates the precipitation pattern centered in the Northwest, where the representation of the orographic enhancement by the forced uplifting during winter (rainy season) is greatly improved over the R-2. The downscaling skill, however, is sensitive to the cumulus parameterization. This sensitivity is studied by comparing the baseline with a branch summer integration replacing the Grell with the Kain–Fritsch cumulus scheme in the CMM5. The dominant EOF mode of the U.S. summer precipitation interannual variation, identified with the out-of-phase relationship between the Midwest and Southeast in observations, is reproduced more accurately by the Grell than the Kain–Fritsch scheme, which largely underestimates the variation in the Midwest. This pattern is associated with east–west movement of the Great Plains low-level jet (LLJ): a more western position corresponds to a stronger southerly flow bringing more moisture and heavier rainfall in the Midwest and less in the Southeast. The second EOF pattern, which describes the consistent variation over the southern part of the Midwest and the South in observations, is captured better by the Kain–Fritsch scheme than the Grell, whose pattern systematically shifts southward.

Impacts of different RCP scenarios on ALADIN-Climate regional climate model projections over Hungary

2020 ◽  
Author(s):  
Beatrix Bán ◽  
Gabriella Zsebeházi
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Horizontal Resolution ◽  
Observation Data ◽  
Rcp Scenarios ◽  
Local Climate ◽  
Temperature And Precipitation ◽  
Local Climate Change ◽  
Primary Basis

<p>The KlimAdat national project was started in 2016 to create a complex database of detailed meteorological information aiming to support local climate change impact studies in different sectors, adaptation strategies and related decision making. Besides observation data its primary basis will be ALADIN-Climate and REMO regional climate model simulations achieved by the Hungarian Meteorological Service and this set of projections will be extended by members of the Euro-CORDEX ensemble in order to quantify the projection uncertainties. <br>This study is focusing on analysis of the ALADIN-Climate model projections driven with RCP4.5 and RCP8.5 scenarios. Firstly, the CNRM-CM5 global model outputs were downscaled to 50 km horizontal resolution over the EURO-CORDEX domain with ALADIN-Climate Version 5.2. Then using these  results as lateral boundary conditions, 10 km experiments were prepared on a domain covering Central and South-Eastern Europe.<br>The presentation aims to introduce the behaviour of these simulations achieved by different scenarios and at different spatial resolution from the aspect of temperature and precipitation change over Hungary. Special attention will be put on the differences in extreme indices. Finally, our 10 km resolution simulations are compared with EURO-CORDEX results to specify their place in a larger ensemble.</p>

scholarly journals Addressing the Issue of Systematic Errors in a Regional Climate Model

2007 ◽  
Vol 20 (5) ◽  
pp. 801-818 ◽  
Author(s):  
Vasubandhu Misra
Keyword(s):  
Regional Climate Model ◽  
Bias Correction ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Circulation Model ◽  
Systematic Errors ◽  
Driver Model ◽  
South American ◽  
Driving Model

Abstract A methodology is proposed in which a few prognostic variables of a regional climate model (RCM) are strongly constrained at certain wavelengths to what is prescribed from the bias-corrected atmospheric general circulation model (AGCM; driver model) integrations. The goal of this strategy is to reduce the systematic errors in a RCM that mainly arise from two sources: the lateral boundary conditions and the RCM errors. Bias correction (which essentially corrects the climatology) of the forcing from the driving model addresses the former source while constraining the solution of the RCM beyond certain relatively large wavelengths in the regional domain [also termed as scale-selective bias correction (SSBC)] addresses the latter source of systematic errors in RCM. This methodology is applied to experiments over the South American monsoon region. It is found that the combination of bias correction and SSBC on the nested variables of divergence, vorticity, and the log of surface pressure of an RCM yields a major improvement in the simulation of the regional climate variability over South America from interannual to intraseasonal time scales. The basis for such a strategy is derived from a systematic empirical approach that involved over 100 regional seasonal climate integrations.

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